1. Field of the Invention
The present invention relates to a color interpolation method, and more particularly, to a color interpolation method capable of more precisely interpolating each of pixels of an image passing through a color filter of Bayer pattern and detected by an image sensor.
2. Description of the Related Art
In general, an image sensor converts brightness and wavelength, of light from an object, detected from pixels to electric values by utilizing a property that a semiconductor reacts to light. The images captured by a digital image storing means with a single complementary metal oxide semiconductor (CMOS) or a charge coupled device (CCD) image sensor equipped therein do not have all of red, green and blue components for each pixel. This is because, in order to realize a color image, the image sensor outputs only one component of the three primary colors from each pixel position using a color filter array composed of red, green and blue.
FIG. 1 exemplifies a color filter array (CFA) having a Bayer pattern. The Bayer pattern is the most generally widely used color filter array, in which a green component accounts for 50% the entire photocells of the color filter, considering that the human visual system is most sensitive to a luminance component, i.e., green, and the rest of the red and blue filters are alternately repeated. Therefore, in order for digital image storing equipment such as digital still cameras, mobile phone cameras and the like to process image signals obtained from the color filter array having such a Bayer pattern, the color component of each of the pixels need to be interpolated to have complete red, green and blue components.
Examining the conventionally generally used technologies for such color interpolation, the most representative methods of low complexity and a decreased load of hardware include nearest neighbor interpolation using the nearest neighbor pixel values of the same color component and bilinear interpolation using an average of pixel values adjacent to a center pixel. In addition, the technology has been advanced to modification of the above-described methods or adoption of the methods in consideration of directivity of horizontal and vertical edges in a certain pixel region. However, despite the simplicity of algorithm, these methods have drawbacks such as false color error and moiré effect, in which a false color is interpolated in an outline or an edge of an object to result in unattractive colors.
In order to improve such drawbacks and increase the capacity of color interpolation, there have been suggested various technologies, which restore colors using more advanced and diverse forms of algorithm based on the importance of pixels in an edge. In these technologies, interpolation for the green channel is completed first and then interpolation for the red and blue channels is performed. However, since these methods disadvantageously require additional memory and increase the load of hardware, they are not readily applicable to color interpolation of color filter array images used for mobile phone cameras. Also, some images according to these methods exhibit false color error or aliasing with partially false colors, despite more complicated algorithm. Furthermore, since the color interpolation methods described above do not consider a noise component obtained from the image sensor at all, the noise component of the image is increased, causing false color error when the algorithm is applied to the inputted image.